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MS data analysis using software such as FragPipe and DIA-NN, as well as basic programming skills in Python. Practical experience in antibacterial assays based on dilution or diffusion methodologies
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sources or related laboratory hardware. You are interested in instrument automation and quantitative data analysis. Experience with Python, LabVIEW, or Matlab for instrument control/data processing is
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machine learning research software, preferably using Python and PyTorch. An interest in foundation models, self supervised learning, multimodal learning, and 3D perception. An affinity for translating
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Science, Mathematics, Statistics, or a closely related field Solid grounding in machine learning and/or probability/statistics Programming proficiency in Python and familiarity with ML frameworks (PyTorch, JAX
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. Ability to develop, understand, and critically evaluate machine learning research software, preferably using Python and PyTorch. An interest in foundation models, self supervised learning, multimodal
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/genome biology, minimum grade B (ECTS grading scale) or equivalent. The Master’s degree must include a thesis of at least 30 ECTS. Programming skills in Python, R or equivalent scientific computing
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chirality, molecular ions, ultrafast optics, or instrumentation will be considered an advantage. Experience with Python programming is also preferred. MSCA Mobility and Eligibility Requirements As the
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Skills/Qualifications Technical Skills: Advanced programming in Python, PyTorch, PyTorch Geometric or DGL. Version control (git), Linux and model training on GPU (reproducible experiments). Other
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highly motivated candidate with: Expertise in cell culture models Experience in molecular biology techniques such as qPCR, western blot, etc. Programming expertise in R and/or Python Comfort working in
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the scenario literature on residual emissions, carbon dioxide removal and carbon capture and storage Proficient programmer, with experience in Python for data analysis (e.g. pandas, pyam) and reproducible